Representative pattern extraction for nucleotide sequence groups using base frequency differences

  • Authors:

  • Kyoung Soon Hwang;Keon Myung Lee;Sung Soo Kim;Chan-Hee Lee;Hyung Woo Yoon;Sung Duk Lee

  • Affiliations:

  • School of Electrical and Computer Engineering, Chungbuk National University, Korea;School of Electrical and Computer Engineering, Chungbuk National University, Korea;School of Electrical and Computer Engineering, Chungbuk National University, Korea;Department of Microbiology, Chungbuk National University, Korea;Department of Clinical Laboratory Science, Juseong College, Korea;Department of Statistics, Chungbuk National University, Korea

  • Venue:
  • CIMMACS'07 Proceedings of the 6th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
  • Year:
  • 2007

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Abstract

Advances in high-throughput technology in molecular biology have been producing lots of sequence data on various organisms. Some organisms like virus have various variances in their nucleotide sequences and could be categorized into several subtypes. A sequential pattern which characterizes a subtype and discriminates it from other subtypes is called signature. This paper proposes a method which extracts signature from a collection of sequences data. Based on position specific relative base frequency deference between one subtype data set and the other subtype data set, the proposed method examines discrimination capabilities for the potential signatures. A tool has been developed which implements the proposed method and applied to an experiment to extract signatures for HIV-1 virus subtypes.